Abstract
The study presents the benchmarking model of rule-based decision tree for higher educational engineering institutions in India based on research performance indicators. The proposed model is built to train the engineering institutions for identifying homogeneous group of institutions in form in clusters. The top 100 engineering institutions ranked in five ranking exercises have been considered for the proposed model. A total of ten featured data variables have been considered as high-dimensional space which are considered as academic and research performance indicators. The principal component analysis is applied to transform the high-dimensional featured data space to principal components with maximum variations explained by featured data variables. Two decision trees are obtained from the proposed model based on the publications indexed in Scopus and citations received against publications. Decision trees are achieved in form of rule-based classifier for grouping cluster of homogeneous engineering institutions based on research performance indicators i.e., publications and citations.
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